Reaction Engineering Approach Research Articles

HHDH-Catalyzed Synthesis of Enantioenriched Fluorinated β-Hydroxy Nitrile─Process Advances through a Reaction Engineering Approach

HHDH-Catalyzed Synthesis of Enantioenriched Fluorinated β-Hydroxy Nitrile─Process Advances through a Reaction Engineering Approach

Establishment of reaction engineering approach for saline droplet and its application in spray evaporation simulation

The statistical study of droplets in spray evaporation tower has guiding significance for understanding spray evaporation and designing drying tower. The key to spray evaporation simulation is establishing a suitable single droplet evaporation model through experiment. In this paper, a visualized single droplet evaporation experiment platform was established. The mass, diameter, and temperature during the evaporation of 10 % NaCl solution droplets were obtained. The Reaction Engineering Approach model was developed and validated to describe the single droplet evolution process in saline water spray. A comparison calculation between the spray evaporation of pure and saline water was executed, and the distributions of residence time of droplets were obtained. It reveals that droplets with initial diameters less than 117 μm can fully evaporate, and for larger droplets, pure water droplets represent a higher evaporation ratio. About 50 % of the fully evaporated saline droplets stay in the backflow area. Contrast numerical experiments of saline water spray evaporation were performed, concluded that similar performance can be attained with the same gas-liquid ratio, and excessive inlet air will reduce the residence time of droplets. The influence of other operating parameters on the performance was also discussed, providing a comprehensive understanding of the regularity of spray drying.

Application prospect of reaction engineering approach in studying drying behavior of single droplet during spray drying of traditional Chinese medicine

Spray drying technology is one of the most commonly used unit operations in the production of traditional Chinese medicine(TCM) preparations, offering advantages such as short drying time and uniform product quality. However, due to the properties of TCM extracts, such as high viscosity, strong hygroscopicity, and poor flowability, there is limited scope to solve the problems of wall adhesion and clumping in spray drying from the macroscopic perspective of pharmaceutical production. Therefore, it has become a trend to study and optimize the spray drying process from the microscopic point of view by investigating single droplet evaporation behavior. Based on the reaction engineering approach(REA), the single droplet drying system, as a novel method for studying droplets, collects parameter data on individual TCM droplets during the drying process and uses the REA to process the data and establish predictive models. This approach is crucial for understanding the mechanism of TCM spray drying. This paper summarized and analyzed the cha-racteristics of various single droplet systems, the application of REA in single droplet drying systems, and its significance in optimizing the process, predicting drying states, and shortening the development cycle in the field of TCM spray drying, and looked ahead to the prospects of this method, including the introduction of new parameters and imaging techniques, aiming to provide a reference for further research in the field of TCM spray drying.

Simulating the Moisture Diffusion and Evaporation of Sawdust during Convective Drying using the Spatial Reaction Engineering Approach

AbstractThe spatial reaction engineering approach (S‐REA) was used to simulate hot air drying of sawdust. The studies extended the previous work reported in literature where the sawdusts were dried using hot air at 70 °C, 80 °C, and 90 °C. The simulated results were found to agree well with the experimental moisture content (R2 > 0.98) and temperature (R2 > 0.82) profiles. In a further analysis using S‐REA, the spatial profiles of moisture content and vapor concentration were generated to understand better the physics behind. Simulation also revealed that the external mass transfer resistance was more dominant as compared to the internal diffusion resistance. The vapor concentrations were observed peaked at time range of about 10 800– 18 000 s and dropped thereafter upon further heating. This observation could be supported by the variation in the vapor effective diffusivities where peak diffusivity values typically occur after most of the moisture evaporates towards the end of drying.

An experimental and numerical study on the brine droplet evaporation considering salt precipitation

Spray evaporation is a promising and highly efficient desalination technology for treating high-salinity wastewater. However, the existing numerical studies on brine spray evaporation are mainly based on pure water assumption and ignore salt precipitation for simplicity. In the present study, the evaporation process of a single brine droplet considering salt precipitation was experimentally investigated using the pendent droplet method. The variation in brine droplet mass during the evaporation and crystallization process was measured for the first time. Based on the experimental data, a reaction engineering approach model for the brine droplets was developed and incorporated into ANSYS Fluent. The obtained reaction engineering approach model was proven compatible with the numerical simulation of brine spray evaporation. Thus, the numerical model was used to compare the spray evaporation behavior between pure water and NaCl solution. Results indicate that brine droplets have larger falling velocities and shorter residence time in the dryer than pure water droplets. The short residence time and large mass transfer resistance of brine droplets lead to a large axial dimension requirement of the dryer. The present study offers a new technological route for the numerical simulation of brine spray evaporation by considering salt precipitation.

Selective Peroxygenase‐Catalysed Oxidation of Toluene Derivates to Benzaldehydes

AbstractBiocatalytic oxidation reactions of toluene derivates to the corresponding aldehydes are typically challenged by regio‐ and chemoselectivity issues. In this contribution we address both challenges by a combined reactant‐ and reaction engineering approach. We demonstrate that the peroxygenase‐catalysed transformation of ring‐substituted toluenes proceeds highly regioselectively in benzylic position. Furthermore, neat reaction conditions not only enable attractive product concentrations (up to 185 mM) but also result in highly chemoselective oxidations to the aldehyde level.

Electrochemical Manufacturing Routes for Organic Chemical Commodities.

Electrochemical synthesis of organic chemical commodities provides an alternative to conventional thermochemical manufacturing and enables the direct use of renewable electricity to reduce greenhouse gas emissions from the chemical industry. We discuss electrochemical synthesis approaches that use abundant carbon feedstocks for the production of the largest petrochemical precursors and basic organic chemical products: light olefins, olefin oxidation derivatives, aromatics, and methanol. First, we identify feasible routes for the electrochemical production of each commodity while considering the reaction thermodynamics, available feedstocks, and competing thermochemical processes. Next, we summarize successful catalysis and reaction engineering approaches to overcome technological challenges that prevent electrochemical routes from operating at high production rates, selectivity, stability, and energy conversion efficiency. Finally, we provide an outlook on the strategies that must be implemented to achieve large-scale electrochemical manufacturing of major organic chemical commodities.

Halohydrin dehalogenase-catalysed synthesis of enantiopure fluorinated building blocks: bottlenecks found and explained by applying a reaction engineering approach

Biocatalytic modification of fluorinated styrene oxide derivatives: improvement of reaction outcome in terms of reaction yield, selectivity and product optical purity by employing reaction engineering approach.

HMSCs in contact with DMSO for cryopreservation: Experiments and modeling of osmotic injury and cytotoxic effect.

In this study a combined analysis of osmotic injury and cytotoxic effect useful for the optimization of the cryopreservation process of a cell suspension is carried out. The case of human Mesenchymal Stem Cells (hMSCs) from Umbilical Cord Blood (UCB) in contact with dimethyl sulfoxide (DMSO) acting as Cryo‐Protectant Agent (CPA) is investigated from the experimental as well as the theoretical perspective. The experimental runs are conducted by suspending the cells in hypertonic solutions of DMSO at varying osmolality, system temperature, and contact times; then, at room temperature, cells are pelleted by centrifugation and suspended back to isotonic conditions. Eventually, cell count and viability are measured by means of a Coulter counter and flow‐cytometer, respectively. Overall, a decrease in cell count and viability results when DMSO concentration, temperature, and contact time increase. A novel mathematical model is developed and proposed to interpret measured data by dividing the cell population between viable and nonviable cells. The decrease of cell count is ascribed exclusively to the osmotic injury caused by expansion lysis: excessive swelling causes the burst of both viable as well as nonviable cells. On the other hand, the reduction of cell viability is ascribed only to cytotoxicity which gradually transforms viable cells into nonviable ones. A chemical reaction engineering approach is adopted to describe the dynamics of both phenomena: by following the kinetics of two chemical reactions during cell osmosis inside a closed system it is shown that the simultaneous reduction of cell count and viability may be successfully interpreted. The use of the Surface Area Regulation (SAR) model recently proposed by the authors allows one to avoid the setting in advance of fixed cell Osmotic Tolerance Limits (OTLs), as traditionally done in cryopreservation literature to circumvent the mathematical simulation of osmotic injury. Comparisons between experimental data and theoretical simulations are provided: first, a nonlinear regression analysis is performed to evaluate unknown model parameters through a best‐fitting procedure carried out in a sequential fashion; then, the proposed model is validated by full predictions of system behavior measured at operating conditions different from those used during the best‐fit procedure.

Spray Drying of PEG6000 Suspension: Reaction Engineering Approach (REA) Modeling of Single Droplet Drying Kinetics

The spray drying technique is suitable for different kinds of liquid dispersions and can be easily optimized to produce solid particles with tailored properties. The spray drying technique is a complex process. As an example, it is difficult to track drying kinetics, shape, and morphological changes on the scale of a single droplet. To better understand the effect of drying process variables on dried particle formation, it is useful to observe the drying of single droplets. Fundamental processes, such as mass and heat transfer, can then be easily monitored and compared with theoretical models. Acoustic levitation enables droplet/particle suspension in the air without any mechanical contact. Experiments in the acoustic levitator can be used to mimic the drying process in the spray dryer. The drying kinetics of single droplets of PEG6000 into solid particles was studied. Droplets with an initial polymer concentration (PEG6000 aqueous solution of 5%, 10%, and 15% (w/w)) were investigated at different gas drying temperatures. The size of the droplet, moisture content, and the shape evolution of the droplet/particle during the drying process were studied. The experimental drying curves were compared with the Reaction Engineering Approach (REA). The REA models were shown to provide a very good agreement for drying behavior, with a relative error of about ±3% between the initial and predicted droplet mass. This model can be implemented into the large-scale modeling of spray drying using Computational Fluid Dynamics (CFD).

Study on drying behavior of additive droplets by reaction engineering approach

A prediction method of drying behaviors for five types of additives droplets based on Reaction Engineering Approach and single droplet drying was introduced in this study. The experimental measurement results showed that the density, viscosity and surface tension of these droplets were in the range of 1.16–1.56 g / m L , 12.86 × 10 − 2 –142.25 × 10 − 2 P a ⋅ s and 35.23–52.05 m N / m , respectively. The volume change rate and drying rate were calculated using machine vision and image processing. The results showed that the volume change rate and the drying rate were in the range of 0.05–16.83 and 1.83 × 10 −3 –7.21 × 10 −3 g / m i n for these five types of additives droplets. The theoretical results showed that the Reynolds number and apparent activation energy ( Δ E v ) were in the range of 0.42–3.54 and 1.88–4.27 k J / m o l for these droplets. The linear relation between heating temperature and Δ E v was established as Δ E v = 111.58 T h − 4709.84 (R 2 = 0.998), indicating that the heating temperature plays a leading role. The prediction method can be applied as a simplified and accurate model to predict drying behaviors based on material specific properties. • The phase transition phenomenon was quantitatively analyzed by using Reaction Engineering Approach. • Drying behavior of additives was studied by single droplet drying using machine vision and image processing. • Heating temperature plays a leading role in the single droplet drying experiment. • Significant linear relationship was found between temperature and apparent activation energy.

Obtaining model parameters of drying kinetics for highly shrinkable materials without knowing the surface area a priori

AbstractShrinkage parameters of highly shrinkable materials such as length, diameter and surface area during drying are difficult to quantify in situ. However, these are significant components of an accurate model. In this study, an attempt to isolate the surface area effect is reported in order to fetch the REA model (reaction engineering approach) parameters without knowing it a priori. Carrot cube and cabbage leaf were selected as experimental material and dried with hot air under a range of conditions. Shrinkages was calculated using an optical method which is used to qualitatively compare with that “calculated” using the current approach. By matching the experimental temperature and moisture content profiles against time after obtaining REA parameters for both samples without knowing the surface area, the surface areas can be “calculated” numerically. Surface area was found to be affected by sample temperature as well as the moisture content. Drying simulations can be well carried out when correlating the surface area against sample moisture content X and temperature T, and it provides the best accuracy in predicting data on T and X vs. time. In addition, carrot cube can shrink ideally while cabbage leaf cannot. The overall relative errors of predicted moisture content and temperature were less than 1%.

Combined infrared and hot air drying (IR-HAD) of sweet potato explored using a multiphase model: application of reaction engineering approach

For better understanding of transport phenomena, local evaporation rate and water vapor concentration should be taken into consideration when predicting drying behavior. However, to the best of our knowledge, there is no model which explicitly represents this. Predictive modeling of combined infrared-heating and hot air drying (IR-HAD) is useful to assist in designing new dryer units and manufacturing the products with desirable quality. As the quality changes are basically local phenomena, the model should be able to capture the local evaporation rate. In this study, for the first, time, spatial reaction engineering approach (S-REA) was developed and used to describe infrared-heating drying of the food materials by using the reaction engineering approach (REA) to represent local evaporation rate. Benchmarks against the single-phase approach and the results showed that the S-REA gave high accuracy toward the experimental data (R2 = 0.978–0.999). The S-REA successfully provided reasonable predictions of two-dimensional (2 D) profiles of moisture content, concentration of water vapor and temperature. This highlights the accuracy of the REA framework to describe the local evaporation rate during the infrared-heating. The REA-based predicted variables can then be applied to project the local quality parameters for quality assurance in food processing. The model is also ready to be used to audit energy demands in drying systems.

Evaporation Characteristics of a Single Desulfurization Wastewater Droplet in High-temperature Gas

Understanding the high-temperature evaporation process of atomized wastewater droplets is a prerequisite for designing an efficient spray evaporation wastewater treatment facility. However, some dynamic characteristics during the evaporation of high-temperature wastewater droplets have not yet been fully understood. Here, the convective evaporation process of desulfurization wastewater droplet in high-temperature gas, which is commonly encountered in the spray drying technology to treat desulfurization wastewater in power plants, was investigated adopting the single droplet drying (SDD) device. In-situ droplet information including the morphology, radius, temperature, and mass was recorded. The influence of bulk temperature and the initial concentration of dissolved solids on evaporation kinetics was studied. To explore the development of resistances during the evaporation process as well as develop a reliable and flexible droplet evaporation model useful for CFD simulations, experimental results were correlated with a modified Reaction Engineering Approach (REA) framework, which revised the previous linear shrinkage model into a hybrid model to illustrate the droplet/particle deformation considering the possible inflation phenomenon at elevated temperatures. The results show that crust formation and internal bubble nucleation induced by wastewater components contributed to unique evaporation features including decreasing evaporation rate and inflation of semi-dried particles. Increasing bulk temperature enhanced the evaporation rate and the degree of inflation. Finally, the rapid and accurate prediction of the modified REA model elucidated its effectiveness to illustrate the whole evaporation and drying process.

Numerical Study and Experimental Validation of Skim Milk Drying in a Process Intensified Counter Flow Spray Dryer

This research presents 3D steady-state simulations of a skim milk spray drying process in a counter-current configuration dryer. A two-phase flow involving gas and discrete phase is modeled using the Eulerian–Lagrangian model with two-way coupling between phases. The drying kinetics of skim milk is incorporated using the Reaction Engineering Approach. The model predictions are found to be in accordance with the experimental temperature measurements with a maximum average error of 5%. The validated computational model is employed further to study the effects of nozzle position, initial spray Sauter Mean Diameter (SMD), air inlet temperature, and feed rate on the temperature and moisture profiles, particle impact positions, drying histories, and product recovery at the outlet. The location of the nozzle upwards (≈23 cm) resulted in maximum product recovery and increased the mean particle residence time at the outlet. A similar trend was observed for the highest feed rate of 26 kg/h owing to the increased spray penetration upstream in the chamber. The maximum evaporation zone was detected close to the atomizer (0–10 cm) when the spray SMD is 38 µm, whereas it shifts upstream (40–50 cm) of the dryer for an SMD of 58 µm. The high air inlet temperature resulted in enhanced evaporation rates only in the initial 10–20 cm distance from the atomizer. The results obtained in this study are beneficial for the development of the novel vortex chamber-based reactors with a counter flow mechanism.

Enhancing Performance of Organic Electrosynthesis through Electrolyte Engineering and Mass Transport Control

Organic electrosynthesis has gained significant interest in pharmaceutical manufacturing over the past decade. This increased interest has been propelled by a proliferation of new green chemical synthesis methods that are highly selective, avoid the use of stoichiometric reducing or oxidizing agents, and reduce the need for downstream separations. Given this recent synthetic advances, reaction engineering approaches start to become important in order to achieve scalable chemical manufacturing processes that operate at high selectivity and high production rates. This presentation will discuss reaction engineering opportunities based on electrolyte design and transport control to enhance the performance of organic electrosynthesis processes. Specifically, I will present our work on understanding and improving the electrohydrodimerization of acrylonitrile (AN) for the production of adiponitrile (ADN) – a model electrochemical processes currently implemented at scale. Although this reaction is the largest and most successful organic electrosynthesis implemented in industry, it faces many challenges owing to its limited energy conversion and selectivity, which are common to reactions of interest in pharmaceutical manufacturing. I will first discuss the role of complex multi-ion electrolyte formulation on the selectivity of this reaction. [1, 2] Specifically, I will discuss the effects that supporting ions play in the electrical double layer (EDL) to control the reactivity of intermediates and direct electrochemical reactions towards desirable reaction pathways. We systematically explored the effects of the size of cations in the electrolyte and show that larger cations enhance selectivity towards ADN by modulating the reactivity of reactants and intermediates in the EDL. Furthermore, we show that intermediate pH regimes (between 7 and 11) are favorable for the production of ADN. Lower pH values enhance the hydrogen evolution reaction (HER) and the hydrogenation of AN, leading to the production of propionitrile (PN). Through the careful formulation of electrolytes, the concentration of reactants, operating current densities, and temperature, ADN selectivities as high as 83% can be achieved at intermediate current densities (- 26 mA cm-2). However, mass transport limitations have proven to be a challenge at high current densities, where the production of propionitrile (PN) dominates.In the second part of the presentation, I will provide experimental insights on how pulsed potential techniques can be used to mitigate mass transport limitations and effectively control the product distribution in ADN electrosynthesis.[3] Electrochemical pulses are used to balance AN diffusive flux to the electrode and its consumption in the electrical double layer (EDL), helping mitigate mass transport limitations at high current densities. This, together with their effect on the interaction between electroactive species and the reaction surface can help improve reaction selectivity. An improvement of over 250% in relative selectivity between ADN:PN was achieved optimizing pulse duration and amplitude, and a 20% increase in ADN production rate was achieved with respect to DC operation. The experimental data obtained for various pulse durations was then used to train machine learning algorithms which identified an optimal pulse sequence with a demonstrated 30% increase in ADN production with respect to DC operation. This new approach to electrosynthesis research which combines electrochemical design principles, judiciously designed experimental campaigns and machine learning can be used to uncover and optimize new electrosynthetic processes in pharmaceutical manufacturing.[1] Blanco, D. E., Dookhith, A. Z., & Modestino, M. A. (2019). Enhancing selectivity and efficiency in the electrochemical synthesis of adiponitrile. Reaction Chemistry & Engineering, 4(1), 8-16.[2] Blanco, D. E., Atwi, R., Sethuraman, S., Lasri, A., Morales, J., Rajput, N. N. and Modestino, M. A. Effect of Electrolyte Cations on Organic Electrosynthesis: The Case of Adiponitrile Electrochemical Production, Journal of The Electrochemical Society, 2020, 167, 155526.[3] Blanco, D. E., Lee, B., & Modestino, M. A. (2019). Optimizing organic electrosynthesis through controlled voltage dosing and artificial intelligence. Proceedings of the National Academy of Sciences, 116(36), 17683-17689.

Spray Drying of Cellulose Nanofibers: Drying Kinetics Modeling of a Single Droplet and Particle Formation

AbstractMicroparticles embedded with cellulose nanofibers (CNFs) are produced via spray drying. The microdroplets are created in the spray dryer by atomization. The solvent evaporates from the droplet, and the dried particles are formed. The drying kinetics on the scale of one droplet is still not well understood. Drying of a single droplet CNF suspension was investigated in an acoustic levitator. The drying kinetics and morphology evolution during the drying process were obtained. The reaction engineering approach (REA) model provided a reasonable prediction of the drying kinetics. An absolute relative error of 2.5 % between the measured initial mass of the droplet and the REA model's estimated value was reported.

Convective drying of highly shrinkable vegetables: New method on obtaining the parameters of the reaction engineering approach (REA) framework

Accurate modeling of fruits and vegetables is difficult due to complications like non-regular shrinkage, wrinkling and skin formation. Comprehensively capturing these changes remain difficult. An interesting pathway through a rearranged set of heat and mass transfer equations to obtain the parameters for the drying kinetics model of the lumped reaction engineering approach (L-REA) is demonstrated. This approach allows the obtainment of REA parameters without worrying about shrinkage in the first place. Carrot, typical of a highly shrinkable vegetable, was dried at temperatures of 43, 55 and 63 °C and a fixed air velocity of 1.5 m/s. The REA parameters reveal a slightly lower additional activation energy compared with that from the classical approach. It can be seen that all moisture content and temperature profiles agree well with experimental data supported by R 2 higher than 0.9959 for moisture and 0.9837 for temperature which validates the proposed new approach is highly feasible for modeling of highly shrinkable vegetables. This work demonstrates the flexibility of the REA framework in avoiding interwinding issues with shrinkage data accuracy and the obtainment of REA parameters when testing highly shrinkable materials. • A new pathway for obtaining REA parameters for highly shrinkable vegetables is demonstrated. • Obtaining the REA parameters without involving surface area information is outlined. • The REA model with accurate data on surface area predicts well the temperature-time and moisture-time profiles.

Vacuum drying of food materials modeled and explored using the reaction engineering approach (REA) framework

REA drying kinetics model has been widely examined for different materials and different operating conditions. Vacuum drying, due to its uniqueness, it presents a challenge for setting up the REA parameters, in particular the specification of the equilibrium activation energy value corresponding to each set of environmental condition. Here, the basic kinetic parameters derived from a convective drying run, is used while the effect of vacuum is captured by the equilibrium activation energy. Upon validation against the experimental data, REA is shown to be applicable. A comparison between the vacuum drying and the convective drying of the same material is also made. The vacuum drying at higher vacuum levels has been predicted, showing the expected behavior. It has been shown that REA is flexible and can be used in vacuum drying related design and optimization studies.

Integrating a model predictive control into a spray dryer simulator for a closed-loop control strategy

Despite the wide-spread applications of spray drying in the production of chemicals, food, and pharmaceuticals, accurate control and development of this unit remains an elusive task because of the complex interactions of variables and phenomena. In this paper, we offer the development of a computationally efficient closed-loop system with a model predictive controller (MPC) where a computational fluid dynamics (CFD) process model is utilized to represent the process behavior. In particular, we present the development of an MPC and its implementation within the CFD model of a lab-scale spray dryer. Dynamic model is created with an adopted CFD model based on a 2D axisymmetric dryer, and Reaction Engineering Approach (REA)- as the drying kinetic method. Then, an MPC control strategy is designed using a linear approximation of a data-driven dynamic model and implemented within the CFD simulation as a user-defined function (UDF). We demonstrate the application of the developed MPC within the CFD simulation to address highly cross-coupled effects among different components of the dryer and guarantee desired product quality measures even in the presence of various disturbances. The proposed MPC embedded CFD modeling tool can serve as an efficient control strategy for other thermo-fluid systems as well.